The motivation behind the study is a stubborn clinical gap. Early childhood is widely recognized as the period in which intervention can most powerfully shape developmental trajectories, yet a formal diagnosis of autism is often not made until around age three. Social-communication differences may be observable long before that, but families and clinicians frequently lack objective, structured ways to capture them. The researchers asked a deceptively simple question: if you go back and watch babies on video, can you see, item by item, which pre-pragmatic and language behaviors were present or absent in those who would later receive an autism diagnosis?

To answer it, the team designed a single-center retrospective case-control study conducted at the Bursa Anka Special Education and Rehabilitation Center in Türkiye between November 2022 and June 2023. They assembled home videos recorded from birth to twelve months of age for thirty children: fifteen who were later diagnosed with ASD and fifteen typically developing (TD) peers. All evaluations relied on pre-existing data sources, including archived video recordings and caregiver-provided contextual information, and no diagnostic or therapeutic intervention was introduced for research purposes. The study received ethical approval from the Istanbul Atlas University Non-Interventional Scientific Research Ethics Committee and was conducted in accordance with the Declaration of Helsinki.

The analytical framework was unusually granular. Rather than assigning a single global score to each child, the researchers coded communication behaviors as simply present or absent using structured checklists across three domains: receptive language, with 61 items; expressive language, with 41 items; and pre-pragmatic skills, the foundational social-communication abilities such as joint attention and gesture use that precede and support pragmatic language, with 19 items. In total, 121 candidate behavioral outcomes were assembled, of which 120 proved analyzable. This item-level approach matters because early autism-related differences are rarely confined to a single behavior; they are distributed across a constellation of subtle social and linguistic signals.

The statistical machinery was equally careful. Between-group differences for each item were tested with two-sided Fisher’s exact tests, a method well suited to small samples and binary outcomes. Effect sizes were estimated as odds ratios with 95 percent confidence intervals, and, crucially, the team applied Benjamini-Hochberg false discovery rate (FDR) correction within each domain. With 120 simultaneous comparisons, uncorrected significance thresholds would inevitably flag many differences by chance alone; the FDR procedure filters out those statistical mirages while retaining genuine signals. The researchers were explicit that the goal was to identify group-level candidate early behavioral indicators, not to evaluate diagnostic or screening accuracy.

The results were striking in both breadth and consistency. Of the 120 analyzable items, 63, or 52.5 percent, differed between the ASD and TD groups at the conventional p < .05 threshold, and 55 items, or 45.8 percent, remained significant after FDR correction. The receptive language domain showed the highest proportion of robust differences, with 35 of 61 items, or 57.4 percent, surviving correction. Expressive language followed with 15 of 41 items, or 36.6 percent, and pre-pragmatic skills with 5 of 18 items, or 27.8 percent. Most telling of all was the directionality: 54 of the 55 FDR-significant items showed lower endorsement in the ASD group. In other words, the differences were not a scattered mix of excesses and deficits but an overwhelmingly one-directional pattern of reduced or absent early communication behaviors.

The prominence of receptive language is particularly noteworthy. Understanding spoken language in the first year of life depends on a web of prerequisite skills: orienting to voices, following a caregiver’s gaze, connecting sounds to objects and events. Decades of research have linked joint attention, the shared focus of two people on an object or event, to later language growth, and prospective studies have shown that infants who later develop autism often show declining attention to eyes and reduced response to their own name within the first two years. The present findings fit squarely within that tradition, but they add something practical: a structured, item-level map of which everyday receptive behaviors, observable in ordinary home footage, most reliably distinguish the two groups at the group level.

The study also connects to a long lineage of home-movie research. Since the early 2000s, investigators have combed family videos of first-birthday parties and everyday play to identify behavioral signs that precede diagnosis, from Osterling and Dawson’s landmark retrospective analyses to computational studies that trained algorithms on parent-infant interactions. What distinguishes the new work is its systematic checklist architecture spanning three communication domains and its rigorous multiple-comparison control, which together reduce the subjectivity that has historically limited retrospective video coding. The approach also complements prospective designs, such as baby-sibling studies, by tapping a naturally occurring record of behavior in children not recruited before birth.

The authors are careful, and rightly so, about what the study does not show. Because the design is retrospective and the sample is small, with fifteen children per group drawn from a single center, the findings identify candidate indicators rather than validated screening tools. Retrospective video analysis carries inherent limitations: footage is not collected systematically, camera angles and recording contexts vary, and the mere presence of a camera can subtly alter family behavior. The researchers explicitly state that their results do not validate a screening or diagnostic method. Instead, they suggest a more modest but still valuable clinical application: retrospective home-video review as an adjunctive tool in developmental history taking, giving clinicians a structured way to mine the visual record that families already possess.

Even with those caveats, the implications are compelling. If a broad swath of early language and pre-pragmatic behaviors is measurably reduced in the first year of life among children later diagnosed with autism, then the window for earlier identification is wider than current diagnostic practice assumes. Earlier detection matters because early behavioral intervention has been shown in meta-analyses to improve social communication outcomes, and the developing brain’s plasticity in infancy offers a developmental opportunity that narrows with time. The next steps are clear from the study’s own framing: larger, multi-center samples; prospective validation of the candidate items; and eventually, perhaps, integration of structured video coding, possibly assisted by computational methods, into routine developmental surveillance. For now, the message is that the first clues may already be sitting in the family video archive, waiting for a careful eye.

Subject of Research: Video-based retrospective analysis of early language and pre-pragmatic communication behaviors in infants later diagnosed with autism spectrum disorder

Article Title: Video-Based Analysis of Language and Pre-Pragmatic Skills for Identifying Autism Risk in Infancy: A Case-Observation Study

Article References: Video-Based Analysis of Language and Pre-Pragmatic Skills for Identifying Autism Risk in Infancy: A Case-Observation Study. (n.d.). https://doi.org/10.1007/s10803-026-07556-1

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07556-1

Keywords: autism spectrum disorder, early identification, home video analysis, receptive language, expressive language, pre-pragmatic skills, infancy, language development, case-control study, developmental screening, joint attention, social communication

The research team, led by Raymond Sturner of the Johns Hopkins University School of Medicine and the Center for Promotion of Child Development through Primary Care, set out to build an optimal algorithm of parent-administered items for detecting both autism and general developmental delay at the 18-month visit. Their starting point was a candid assessment of why existing screens fall short. The Modified Checklist for Autism in Toddlers, Revised with Follow-Up (M-CHAT-R/F), the most widely used autism screener, has documented weaknesses at this young age. Its positive predictive value drops sharply in younger toddlers, with community samples reporting values as low as .28 to .36 at around 18 months compared with .61 to .69 in older children. The required follow-up interview, designed to rescue that predictive value, is rarely completed in real primary care, and even research studies apply it inconsistently.

There is a deeper structural problem, too. Validation studies of the M-CHAT-R/F have generally not included diagnostic evaluations of representative samples of children who passed the screen, which makes honest estimates of sensitivity and specificity nearly impossible. Prior work by the same team, drawing on a large community sample that included matched screen-negative children, found the sensitivity of the M-CHAT-R/F to be just .36, well below the Q-CHAT-10-O, an ordinally scored version of the Quantitative Checklist for Autism in Toddlers, which reached .63 with half the items and no follow-up interview. No autism screen for the 18-month age group has ever achieved the generally recommended performance benchmark of greater than .70 for both sensitivity and specificity in community samples, for autism or for developmental delay.

The new study took an unusually ambitious approach to item selection. Rather than writing questions from scratch, the researchers curated candidate items from the most commonly used autism screens, including the M-CHAT-R/F, the Parent’s Observation of Social Interaction, and the Q-CHAT-10-O, and supplemented them with items drawn from longitudinal studies of children at elevated likelihood for autism: the First Year Inventory developed at the University of North Carolina and the Parent Observation of Early Markers Scales from Brock University. They also included expressive vocabulary items from the MacArthur-Bates Communicative Development Inventory (MCDI), because prior work had shown that vocabulary production is a powerful contributor to autism prediction around 18 months, even though expressive language delay is not itself a DSM-5 diagnostic criterion for autism.

The scale of the community data collection was substantial. Parents of 11,878 children aged 16 to 20 months, recruited from research-enrolled community pediatric offices in Maryland, Massachusetts, and North Carolina, completed the M-CHAT-R, the Q-CHAT-10, and the age-appropriate Ages and Stages Questionnaires-3 through an online screening system before scheduled 18-month visits. From the 787 children with any positive screen, plus matched controls who passed both screens, the team enrolled families willing to undergo full diagnostic testing. After exclusions and attrition, the final sample comprised 408 children with complete data on key measures and confirmed case status. Diagnostic evaluations used the ADOS-2 Toddler Module administered by testers blind to screening results, together with the Mullen Scales of Early Learning. Developmental delay was defined using criteria that mirror the thresholds most states apply for early intervention eligibility.

The analytical machinery was equally distinctive. The team fitted the MCDI Words and Sentences vocabulary data, obtained from the open Wordbank database, to a Rasch measurement model in which individual words carry difficulty scores on the same logit scale as toddler ability estimates. That allowed them to build a computerized adaptive testing version of the vocabulary checklist, in which each word presented depends on the respondent’s previous answers, cutting response burden while simulation studies confirmed the short form retained high person reliability of .98 and person separation of 6.78. For classification, they applied gradient-boosted tree modeling with feature selection via the Boruta method and Shapley values, plus Bayesian hyperparameter optimization. To guard against machine learning capitalizing on chance associations, models were trained on a synthetic dataset of 25,000 cases generated from roughly half the authentic data, validated on a synthetic set of 12,500 cases, and then evaluated on an authentic holdback sample of 202 children.

The resulting instrument, which the authors call the Toddler Autism and Developmental Adaptive Screen, distills the candidate pool down to just 19 features. The final model is anchored by expressive vocabulary percentile and items representing joint attention, the cluster of behaviors, pointing to share interest, following a point, showing objects just to share, and shifting eye gaze to check a parent’s reaction, that decades of prospective sibling studies have identified as the earliest and most consistent emerging signs of autism. Other retained items probe pretend play, unusual finger movements, sensitivity to noise, and imitation of household activities. Notably, the machine learning process retained some redundant content in multiple wordings from different source instruments, which the authors interpret as reflecting both the clinical importance of those topics and the value of asking things in several ways to ensure accurate parent report.

The performance numbers are the headline. On the authentic holdback sample, the new model’s sensitivity for autism reached .77, compared with .36 for the M-CHAT-R/F administered to the same children, roughly a doubling of detection rate. It also outperformed the Q-CHAT-10-O (.77 versus .63) in this 16-to-20-month age group. For developmental delay, the screen achieved sensitivity and specificity both above .70, with a positive predictive value of .60, and proved twice as sensitive as the standard ASQ-3 general developmental screen (.73 versus .39) against state early intervention eligibility criteria. The authors report that the tool appears to be the only screen for this age with generally recommended performance, over .70 on both sensitivity and specificity, for both autism and developmental delay simultaneously. Positive predictive value for autism, at .37, was not significantly higher than the M-CHAT-R/F’s, a reminder that no screening tool escapes the base-rate problem entirely.

One of the most conceptually interesting findings concerns how the same items behave differently depending on the outcome being predicted. Twelve items were identified for detecting developmental delay, half of them overlapping with the autism item set, yet none are weighted the same way for the two purposes, and one item about favorite activities even flips its meaning, with reading books weighting toward delay and lining up objects weighting toward autism. Rather than relying on simple cut scores, the model weights each feature in combination with the others, mirroring the way autism is clinically defined as a syndrome of features rather than a single deficit. The authors emphasize that the instrument is intended as a primary screening tool, not a diagnostic one, producing a pass or fail for autism, a separate pass or fail for developmental delay, and an expressive vocabulary percentile for age.

Practical advantages could matter as much as raw accuracy. The entire screen consists of 18 standard items plus an adaptive vocabulary measure capped at 25 words, where the current standard practice of administering both the M-CHAT-R and the ASQ-3 requires 50 caregiver items plus a follow-up interview that often never happens. No follow-up interview is needed, results can integrate with electronic health records, and smartphone administration makes the approach feasible even in low-income settings. The authors are candid about limitations: the sample over-represented highly educated parents, attrition affected both screen-positive and screen-negative groups, children exposed to English less than half the time were excluded, and not every child with autism is detectable at 18 months, so continued surveillance at older ages remains essential. The assembled tool is now being tested in a larger, more socioeconomically diverse community sample. If those results replicate, the humble parent questionnaire, retooled with item response theory and machine learning, could become one of the most consequential screening advances in early child development.

Subject of Research: Machine learning-based parent-report screening for autism and developmental delay at the 18-month pediatric visit

Article Title: Exploring the Potential of Parent Report for Autism/Developmental Screening at the 18-Month Visit

Article References: Exploring the Potential of Parent Report for Autism/Developmental Screening at the 18-Month Visit. (n.d.). https://doi.org/10.1007/s10803-026-07472-4

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07472-4

Keywords: autism screening, developmental delay, M-CHAT, 18-month visit, parent report, machine learning, early intervention, joint attention, expressive vocabulary, pediatrics, computerized adaptive testing, Q-CHAT

Joint attention, the shared focus of two people on the same object or event, typically emerges in infants between eight and fifteen months of age and serves as a developmental gateway to language, social referencing, and perspective-taking. Children with autism spectrum disorder (ASD) frequently show delays in the components of responding to joint attention, or RJA, including eye contact, gaze shifting, and pointing. Because these deficits ripple outward into later language and social development, researchers have long sought efficient, practical ways to strengthen them.

The study, conducted by Martha Pelaez of Florida International University, Carolyn Crysdale of Endicott College, and Katerina Monlux of Oslo Metropolitan University, asked a deceptively simple question: can social consequences alone—praise and smiles delivered contingently—increase joint attention responses in five- and six-year-old children with ASD, and how do they compare with social stimuli paired with tangible reinforcers? Previous work suggested that for children with autism, social stimuli might need to be explicitly conditioned with primary reinforcers before they could support learning, and most prior interventions relied on edibles or toys.

To answer the question, the researchers used a single-subject multiple treatment reversal design with counterbalanced treatment order. Three children completed the sequence baseline, social-only treatment, withdrawal, and social-plus-tangible treatment, while three others received the treatments in the reverse order. Across sessions held in a public kindergarten classroom in Florida and two early intervention clinics in Florida and Maryland, children sat across a table from an interventionist with three upside-down plastic cups, one of which concealed a small toy car. Each trial began with the cue “look at me,” after which the interventionist shifted gaze toward the target cup and returned eye contact. A correct response required the child to make eye contact, follow the gaze shift, re-establish eye contact, and point to the correct cup within thirty seconds.

In the social-only condition, correct responses were followed immediately by a smile and the praise “Good job.” In the combined condition, the same social consequences were delivered simultaneously with a tangible item such as a small toy. During baseline and withdrawal phases, no reinforcement or prompting was provided. Sessions lasted roughly twenty to thirty minutes and included four to six blocks of ten trials each, with interobserver agreement coded on 39 percent of sessions and procedural fidelity averaging 100 percent on checked trials.

The results were striking in their consistency. Every participant increased one or both components of responding to joint attention during the contingent social-stimuli condition relative to baseline and withdrawal phases. Gaze shifting and pointing percentages rose substantially across children: one boy’s gaze shifting climbed from a baseline mean of 27 percent to 63 percent under social reinforcement alone, while another child’s gaze shifting rose from 37 percent to 87 percent, reaching ceiling levels of 100 percent in some sessions. A girl included in the sample, who showed limited gaze shifting despite high pointing accuracy, improved her gaze shifting from a mean of 68 percent to 93 percent in the combined condition.

Notably, the social-plus-tangible condition often produced the highest levels of responding, but not invariably. Two children performed as well or slightly better with social stimuli alone, and the relative advantage of the combined condition varied across participants and response components. The authors emphasize that the principal contribution of the study is not that tangible stimuli enhanced responding, but that contingent social stimuli by themselves were sufficient to produce meaningful gains—a finding that challenges the assumption that tangible reinforcers are necessary for teaching joint attention to children with autism.

The researchers interpret their findings through the lens of conditioned reinforcement and stimulus control. Social stimuli such as smiles, praise, and eye contact do not acquire their behavioral effects independently of experience; through repeated pairings with feeding, comfort, play, and assistance during early development, initially neutral social events can become conditioned reinforcers. Because the children in this study had histories of interacting with teachers and clinicians who delivered praise, the contingent social consequences likely already functioned as reinforcers. The timing mattered as well: praise was delivered specifically after the child completed the full response sequence, strengthening the temporal and functional relation between the child’s gaze shifting, pointing, and the social outcome.

The findings also align with developmental accounts of joint attention, particularly the distinction between responding to joint attention, which is tied to attention regulation and the processing of externally generated social cues, and initiating joint attention, which reflects self-generated social motivation. By strengthening children’s ability to discriminate, follow, and respond to another person’s attentional directives, the intervention may expand each child’s access to socially mediated learning opportunities beyond the structured session itself, complementing operant and developmental perspectives at compatible levels of analysis.

The authors acknowledge limitations, including the small heterogeneous sample, the absence of follow-up sessions to assess maintenance and generalization, and the inclusion of one participant without a formal ASD diagnosis. Each treatment condition was also implemented only once per child, leaving open questions about sequence and carryover effects. Still, the practical implications are considerable. Before adding toys or edibles, practitioners may wish to assess whether a child’s existing history has given smiles and praise reinforcing value, since a separate formal conditioning phase may be unnecessary for many learners. Future research, the team suggests, should directly evaluate which forms of social stimulation function as reinforcers for individual children, examine whether improvements in joint attention translate into language gains over time, and test caregiver-implemented versions of the procedure in homes and classrooms where joint attention naturally unfolds.

Subject of Research: Using contingent social stimuli as reinforcers to increase responding to joint attention in children with autism spectrum disorder

Article Title: Increasing Joint Attention in Children With Autism Using Contingent Social Stimuli as Reinforcers

Article References: Increasing Joint Attention in Children With Autism Using Contingent Social Stimuli as Reinforcers. (n.d.). https://doi.org/10.1007/s10803-026-07524-9

Image Credits: AI Generated

DOI: 10.1007/s10803-026-07524-9

Keywords: autism spectrum disorder, joint attention, responding to joint attention, gaze shifting, pointing, contingent social stimuli, social reinforcement, tangible reinforcers, conditioned reinforcement, applied behavior analysis, early intervention, children with autism